code: def convert_x_to_bbox(x, score=None):
      """
      Takes a bounding box in the centre form [x,y,s,r] and returns it in the form
        [x1,y1,x2,y2] where x1,y1 is the top left and x2,y2 is the bottom right
      """
      w = np.sqrt(x[2] * x[3])
      h = x[2] / w
      if score == None:
          return np.array(
              [
                  x[0] - w / 2.0,
                  x[1] - h / 2.0,
                  x[0] + w / 2.0,
                  x[1] + h / 2.0,
              ]
          ).reshape((1, 4))
      else:
          score = np.array([score])
          return np.array(
              [
                  x[0] - w / 2.0,
                  x[1] - h / 2.0,
                  x[0] + w / 2.0,
                  x[1] + h / 2.0,
                  score,
              ]
          ).reshape((1, 5))
  
file_path: PaddleDetection/deploy/pptracking/python/mot/tracker/ocsort_tracker.py
imports: import time
  import numpy
  from ..matching.ocsort_matching import associate, linear_assignment, iou_batch, associate_only_iou
  from ..motion.ocsort_kalman_filter import OCSORTKalmanFilter
label_desc: Use image node_id 3 for calling a global function with example usage: convert_x_to_bbox(x, score) and returns: np, np